scholarly journals Malaysian Business Community Social Network Mapping on the Web Based on Improved Genetic Algorithm

10.5772/9556 ◽  
2010 ◽  
Author(s):  
Siti Nurkhadijah Aishah Ibrahim ◽  
Ali Selamat ◽  
Mohd Hafiz
Keyword(s):  
Genetic Algorithm ◽  
Social Network ◽  
Business Community ◽  
Improved Genetic Algorithm ◽  
Web Based ◽  
Network Mapping ◽  
The Web

scholarly journals Extracting a Heterogeneous Social Network of AcademicResearchers on the Web Based on Information Retrieved from Multiple Sources

2011 ◽  
Vol 01 (02) ◽  
pp. 33-38 ◽  
Author(s):  
Rasim M. Alguliev ◽  
Ramiz M Aliguliyev ◽  
Fadai S Ganjaliyev
Keyword(s):  
Social Network ◽  
Multiple Sources ◽  
Web Based ◽  
Heterogeneous Social Network ◽  
The Web

LEARNING ENGLISH VOCABULARY USING WEB-BASED LEITNER BOX WITH SOCIAL NETWORK

2015 ◽  
Vol 77 (33) ◽  
Author(s):  
Yunxia Gao ◽  
Zaidatun Tasir ◽  
Jamalludin Harun ◽  
Nurul Farhana Jumaat
Keyword(s):  
Social Network ◽  
Collaborative Learning ◽  
Learning Environment ◽  
Positive Impact ◽  
Vocabulary Learning ◽  
Structured Interviews ◽  
Web Based ◽  
Collaborative Learning Environment ◽  
The Impact ◽  
The Web

The aim of the research is to explore the impact of the web-based Leitner Box which is enhanced with social network, particularly Facebook on English vocabulary learning. This research used mixed research design and the data were collected both in qualitative and quantitative ways. The instruments include questionnaire, semi-structured interviews, and performance tests. 35 university’s students were chosen randomly as the respondents for the questionnaire and 30 students from English class were chosen purposively to do the pre-test and post-test. From the findings, it is discovered that students agreed they have problems in learning vocabulary (mean = 3.98).   The web-based Leitner Box has a significant positive impact on English vocabulary learning (p<0.05). Findings from the questionnaires also revealed that students gave positive opinions toward web-based Leitner box (mean = 4.28).  In term of whether the element of social network can be beneficial to students, the findings showed that social network helps students to learn English vocabulary in this collaborative learning environment (mean = 4.28). The students claimed that web-based Leitner Box and social network make the vocabulary learning process much easier and more interesting by sharing information and actively participating in the collaborative learning environment.

A Web-Based Platform for Modular Design of Intelligent Instrument Based on Improved Genetic Algorithm

2011 ◽  
Vol 88-89 ◽  
pp. 291-295
Author(s):  
Jian Pan ◽  
Guo Hong Mao ◽  
Jin Xiang Dong
Keyword(s):  
Genetic Algorithm ◽  
Modular Design ◽  
Optimal Solutions ◽  
Improved Genetic Algorithm ◽  
Web Database ◽  
User Requirement ◽  
Web Based ◽  
Encoding Scheme ◽  
Intelligent Instrument ◽  
Selection Of

The design of new products is a creative work based on designer’s knowledge or experience. This paper develops a web-based design platform for intelligent instrument with the technology of Java and web database. It aims at offering near-optimal solutions of product design scheme that meets user requirement with the selection of module. An improved genetic algorithm with a binary encoding scheme is proposed to accomplish the selection of module more effectively.

scholarly journals The dynamics of Web-based social networks: Membership, relationships, and change

First Monday ◽  
2007 ◽  
Author(s):  
Jennifer Golbeck
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Social Information ◽  
Great Promise ◽  
Relationship Dynamics ◽  
Web Based ◽  
The Public ◽  
Comprehensive Survey ◽  
The Media ◽  
The Web

Social networks on the Web are growing dramatically in size and number. The huge popularity of sites like MySpace, Facebook, and others has drawn in hundreds of millions of users, and the attention of scientists and the media. The public accessibility of Web&#150;based social networks offers great promise for researchers interested in studying the behavior of users and how to integrate social information into applications. However, to do that effectively, it is necessary to understand how networks grow and change. Over a two&#150;year period we have collected data on every social network we could identify, and we also gathered daily information on thirteen networks over a 47&#150;day period. In this article, we present the first comprehensive survey of Web&#150;based social networks, followed by an analysis of membership and relationship dynamics within them. From our analysis of these data, we present several conclusions on how users behave in social networks, and what network features correlate with that behavior.

scholarly journals Integrating a Web-Based Self-Management Tool (Managing Joint Pain on the Web and Through Resources) for People With Osteoarthritis-Related Joint Pain With a Web-Based Social Network Support Tool (Generating Engagement in Network Involvement): Design, Development, and Early Evaluation

10.2196/18565 ◽  
2020 ◽  
Vol 4 (11) ◽  
pp. e18565
Author(s):  
Paul Clarkson ◽  
Ivaylo Vassilev ◽  
Anne Rogers ◽  
Charlotte Brooks ◽  
Nicky Wilson ◽  
...  
Keyword(s):  
Social Network ◽  
Focus Groups ◽  
Goal Setting ◽  
Joint Pain ◽  
Management Tool ◽  
Self Management ◽  
Small Scale ◽  
Web Based ◽  
Scale Evaluation ◽  
The Web

Background Joint pain caused by osteoarthritis (OA) is highly prevalent and can be extremely debilitating. Programs to support self-management of joint pain can be effective; however, most programs are designed to build self-efficacy and rarely engage social networks. Digital interventions are considered acceptable by people with joint pain. However, many existing resources are not accessible for or developed alongside people with lower health literacy, which disproportionately affects people with OA. Objective This study aims to design and develop an accessible digital self-management tool for people with joint pain and integrate this with an existing social network activation tool (Generating Engagement in Network Involvement [GENIE]) and to explore the feasibility of these linked tools for supporting the management of joint pain. Methods The study was conducted in 2 phases: a design and development stage and a small-scale evaluation. The first phase followed the person-based approach to establish guiding principles for the development of a new site (Managing joint Pain On the Web and through Resources [EMPOWER]) and its integration with GENIE. People with joint pain were recruited from libraries, a community café, and an exercise scheme to take part in 3 focus groups. EMPOWER was tested and refined using think-aloud interviews (n=6). In the second phase, participants were recruited through the web via libraries to participate in a small-scale evaluation using the LifeGuide platform to record use over a 1-month period. Participants (n=6) were asked to complete evaluation questionnaires on their experiences. The NASSS (nonadoption, abandonment, scale-up, spread, and sustainability) framework was used to explore the feasibility of the sites. Results The focus groups established guiding principles for the development of the tool. These included ensuring accessibility and relevance for people with OA-related joint pain and recognizing that joint pain is the reason for seeking support, trust, social facilitation, and goal setting. Think-aloud interviews identified issues with user experience and site navigation and the need for professional input for referral and goal setting, confusion, and tensions over the role of GENIE and site connectivity. Participants expected the sites to be specific to their pain-related needs. EMPOWER was accessed 18 times; 6 users registered with the site during the evaluation study. Participants mostly explored information pages on being active and being a healthy weight. Only one participant undertook goal setting and 4 participants visited the GENIE website. Conclusions Using the NASSS framework, we identified the complexity associated with integrating EMPOWER and GENIE. The value proposition domain highlighted the technical and conceptual complexity associated with integrating approaches. Although identified as theoretically achievable, the integration of differing propositions may have caused cognitive and practical burdens for users. Nevertheless, we believe that both approaches have a distinct role in the self-management of joint pain.

scholarly journals Optimization Strategy of IoT Sensor Configuration Based on Genetic Algorithm-Neural Network

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Yuanyuan Yang
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Data Communication ◽  
Piezoelectric Sensor ◽  
Sensor Data ◽  
Improved Genetic Algorithm ◽  
Management Platform ◽  
Sensor Configuration ◽  
Web Management ◽  
The Web

This article carries out the overall design framework of the IoT sensor data processing platform and analyzes the advantages of using the integrated construction platform. The platform is divided into two parts, a web management platform and a data communication system, and interacts with the database by integrating the business layers of the two into one. The web management platform provides configurable communication protocol customization services, equipment information, personal information, announcement information management services, and data collection information monitoring and analysis services. The collected data is analyzed by the sensor data communication service system and then provided to the web management platform for query and call. This paper discusses the theoretical basis of the combination of genetic algorithm and neural network and proposes the necessity of improving genetic algorithm. The improved level involves chromosome coding methods, fitness function selection, and genetic manipulation. We propose an improved genetic algorithm and use an improved genetic algorithm (IGA) to optimize the neural network structure. The finite element method is adopted, the finite element model is established, and the shock piezoelectric response is numerically simulated. The genetic neural network method is used to simulate the collision damage location detection problem. The piezoelectric sensor is optimized, and the optimal sensor configuration corresponding to its initial layout is obtained, which provides guidance for the optimal configuration of the actual piezoelectric sensor.

scholarly journals Integrating a Web-Based Self-Management Tool (Managing Joint Pain on the Web and Through Resources) for People With Osteoarthritis-Related Joint Pain With a Web-Based Social Network Support Tool (Generating Engagement in Network Involvement): Design, Development, and Early Evaluation (Preprint)

2020 ◽  
Author(s):  
Paul Clarkson ◽  
Ivaylo Vassilev ◽  
Anne Rogers ◽  
Charlotte Brooks ◽  
Nicky Wilson ◽  
...  
Keyword(s):  
Social Network ◽  
Focus Groups ◽  
Goal Setting ◽  
Joint Pain ◽  
Management Tool ◽  
Self Management ◽  
Small Scale ◽  
Web Based ◽  
Scale Evaluation ◽  
The Web

BACKGROUND Joint pain caused by osteoarthritis (OA) is highly prevalent and can be extremely debilitating. Programs to support self-management of joint pain can be effective; however, most programs are designed to build self-efficacy and rarely engage social networks. Digital interventions are considered acceptable by people with joint pain. However, many existing resources are not accessible for or developed alongside people with lower health literacy, which disproportionately affects people with OA. OBJECTIVE This study aims to design and develop an accessible digital self-management tool for people with joint pain and integrate this with an existing social network activation tool (Generating Engagement in Network Involvement [GENIE]) and to explore the feasibility of these linked tools for supporting the management of joint pain. METHODS The study was conducted in 2 phases: a design and development stage and a small-scale evaluation. The first phase followed the person-based approach to establish guiding principles for the development of a new site (Managing joint Pain On the Web and through Resources [EMPOWER]) and its integration with GENIE. People with joint pain were recruited from libraries, a community café, and an exercise scheme to take part in 3 focus groups. EMPOWER was tested and refined using think-aloud interviews (n=6). In the second phase, participants were recruited through the web via libraries to participate in a small-scale evaluation using the LifeGuide platform to record use over a 1-month period. Participants (n=6) were asked to complete evaluation questionnaires on their experiences. The NASSS (nonadoption, abandonment, scale-up, spread, and sustainability) framework was used to explore the feasibility of the sites. RESULTS The focus groups established guiding principles for the development of the tool. These included ensuring accessibility and relevance for people with OA-related joint pain and recognizing that joint pain is the reason for seeking support, trust, social facilitation, and goal setting. Think-aloud interviews identified issues with user experience and site navigation and the need for professional input for referral and goal setting, confusion, and tensions over the role of GENIE and site connectivity. Participants expected the sites to be specific to their pain-related needs. EMPOWER was accessed 18 times; 6 users registered with the site during the evaluation study. Participants mostly explored information pages on being active and being a healthy weight. Only one participant undertook goal setting and 4 participants visited the GENIE website. CONCLUSIONS Using the NASSS framework, we identified the complexity associated with integrating EMPOWER and GENIE. The value proposition domain highlighted the technical and conceptual complexity associated with integrating approaches. Although identified as theoretically achievable, the integration of differing propositions may have caused cognitive and practical burdens for users. Nevertheless, we believe that both approaches have a distinct role in the self-management of joint pain. CLINICALTRIAL

scholarly journals The Effect of Social Network on Retail Buying Behaviour in Chennai City

2019 ◽  
Vol 8 (4S3) ◽  
pp. 1-4
Keyword(s):  
Foreign Direct Investment ◽  
Social Network ◽  
Mass Media ◽  
Information Seeking ◽  
Direct Investment ◽  
Web Based ◽  
Social Measurement ◽  
Buying Behaviour ◽  
Chennai City ◽  
The Web

Retail is one of the significant sectors in India seeking attention for the investment. It is also approaching a lot of foreign direct investment. A blast of societal mass media networks, in the last decade has erupted tradition information seeking in market. Online networking, for example, Face book twitter, you tube, and Google has added another social measurement to the web. This paper depends on impact of web based life on retail purchasing conduct.

Study on the Stability of Virtual Network Mapping Algorithm Based on the Improved Genetic Algorithm

2014 ◽  
Vol 926-930 ◽  
pp. 3696-3700
Author(s):  
Jun Wei Ge ◽  
Yun Yu ◽  
Yi Qiu Fang
Keyword(s):  
Genetic Algorithm ◽  
Virtual Network ◽  
Improved Genetic Algorithm ◽  
Mapping Algorithm ◽  
Control Threshold ◽  
Physical Node ◽  
Virtual Network Mapping ◽  
The Stability ◽  
Network Mapping ◽  
Virtual Mapping

A based on the improved genetic algorithm of the stability is presented, for the current virtual network mapping study based on the underlying resources load imbalance. The algorithm consider for the constraint of the underlying physical node, link resources and the parameters of virtual network requests. Join control threshold α to decide to accept the request. Use the improved genetic algorithm to automatically adapt to the current load overheating network node, choose the best physical link and line up a virtual mapping. As can be seen through the analysis of simulation results, the algorithm can process the request maps faster than others algorithm, improve the stability and the load balancing capability.

A Web-Based Platform for Intelligent Instrument Design Using Improved Genetic Algorithm

2012 ◽  
Vol 7 (10) ◽  
Author(s):  
Jian Pan ◽  
Guohong Mao ◽  
Jinxiang Dong
Keyword(s):  
Genetic Algorithm ◽  
Instrument Design ◽  
Improved Genetic Algorithm ◽  
Web Based ◽  
Intelligent Instrument
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